1056 research outputs found
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Dataset for "Optimisation of the cladding structure to minimise surface roughness scattering in antiresonant, hollow-core fibres"
No full textThe dataset consists of three spreadsheets that contain all the data used to generate Figures 2, 3 and 4 of the paper, "Optimisation of the cladding structure to minimise surface roughness scattering in antiresonant, hollow-core fibres". All the results were generated with the finite element simulation code COMSOL Multiphysics 6.3. The data consists of the real and imaginary parts of the effective index, together with computed values of the normalised electric field intensity, F, for each boundary and component in the relevant fibre structure, as described in the paper. The raw values of F are scaled by dividing by (wavelength^2)/(core_radius^3) (as described in the paper), and so all the data values are dimensionless.All the results given in the dataset were generated with the finite element simulation code COMSOL Multiphysics 6.3. Details of the calculations are given in the paper.COMSOL Multiphysics 6.
Dataset for the journal paper "Are simple models for natural ventilation suitable for shelter design?"
No full textThis dataset contains the annual simulation results for a single-room shelter under five natural ventilation scenarios (S01-S05), and located in Hitsats (Ethiopia). The simulations have been run using both EnergyPlus AirflowNetwork (AFN) and Contam. The dataset contains the results of outdoor temperature, wind speed and direction, relative humidity, indoor temperature, wind speed at the shelter, indoor concentration of carbon dioxide (CO2), natural ventilation and infiltration.The dataset has been created through airflow building simulation using EnergyPlus AirflowNetwork (AFN) and Contam. The case study is represented by a single-room shelter located in Hitsats (Ethiopia). Five ventilation layouts: single-side ventilation wind-driven, cross-ventilation wind-driven, single-side ventilation buoyancy-driven, single-side two windows buoyancy-driven, and cross-ventilation buoyancy-driven.The simulations have been run using EnergyPlus v.22.2 and Contam 3.4.0.1.The data are organised in five sheets (S01-S05), one for each ventilation type: single-side ventilation wind-driven (S01), cross-ventilation wind-driven (S02), single-side ventilation buoyancy-driven (S03), single-side two windows buoyancy-driven (S04)and cross-ventilation buoyancy-driven (S05)
Dataset for "DNA Sensing with Whispering Gallery Mode Microlaser"
No full textNucleic acid sensing is crucial for advancing diagnostics, therapeutic monitoring and molecular biology research, by enabling the precise identification of DNA and RNA interactions. Here, we present an innovative sensing platform based on DNA-functionalized whispering gallery mode (WGM) microlasers. By correlating spectral shifts in laser emission to changes in refractive index, we demonstrate real-time detection of DNA hybridization and structural changes. The addition of gold nanoparticles to the DNA strands significantly enhances sensitivity, and labelling exclusively the sensing strand or a hairpin strand eliminates the need for secondary labelling of the target strand. We further show that ionic strength influences DNA compactness, and we introduce a hairpin-based system as a dual-purpose sensor and con-trolled release mechanism for potential drug delivery. This versatile WGM-based platform offers promise for sequence-specific nucleic acid sensing, multiplexed detection, and in vivo applications in diagnostics and cellular research.
This dataset includes the data from Figures 1-5 of the associated paper. It is organised into folders by figure number for easy navigation, with filenames indicating the corresponding figure and identifying letters (e.g., a, b, c, d). For details on how the data was collected refer to publication and its supplementary information.The methodology can be found in the associated paper
Multi-Modal Dataset for "Towards Robust Surface Electromyography for Upper Limb Protheses using Machine Learning "
No full textThe dataset contains sEMG recordings from 10 anatomically intact participants. The data is separated into 13 trials, 11 of which were performed under manual intervention to vary one of the following parameters: Skin Temperature, Arm Position, Electrode Position, Impedance. Within each trial the participants perform 2 repetitions of 6 different hand grasps, held for 5 seconds.
The data was recorded using custom-built sEMG sensors that also permitted the recording of skin temperature and skin-electrode impedance. Recordings of these features are provided with the data, recorded following the completion of a grasp.
The data were recorded following approval granted by the University of Bath Research Ethics Approval Committee for Health, study ID: EP 23 019.The data were collected using 2 custom-built sEMG sensors from the participant's forearm, placed on the flexor carpi ulnaris and the extensor carpi radialis of each participant. The sEMG data was collected at 500 Hz, with an onboard 1st-order Bandpass filter at 4.82 and 241.1 Hz applied before digital conversion. A gain of 162.5 is applied to the data. The data were recorded in an unregulated environment. The sEMG data provided are as recorded, no further filtering has been applied.
For each participant, 13 recording trials were performed, in each the participant performed 2 repetitions of 6 different hand gestures, picking up appropriate objects to perform the gestures. Image depictions of the gestures can be found alongside the data. Participants performed the gestures for approximately 5 seconds, followed by approximately 11 seconds of rest. Over the first 5 seconds of the rest period the sEMG sensors do not record, and instead a skin temperature and a skin-electrode impedance recording are made by the custom sensor units. The 12 temperature and impedance data are stored within the same .mat file as the sEMG data for each trial. Temperature data is recorded in Celsius, impedance in ohm and phase angle pairs per channel, and the sEMG data is recorded in Volts. Accompanying each set of data is additionally vectors indicating the gesture being performed (or rest where appropriate) and whether it is repetition one or two, these allow for the generation of training and testing datasets for pattern recognition applications.
The 13 recording trials include: 2 control trials, 2 trials in which the participant arm temperature was varied, 2 trials in which the skin-electrode impedance was changed, 3 trials in which the participant varies the arm's position, and 4 trials in which the electrodes position is shifted relative to the base position. Each trial is stored within its own recording file in the dataset, and the details of the trial order and name are presented in the accompanying text file
gorkemanil/Temperature-Prediction-of-Polymers-using-IR-Spectra-and-Fingerprint-Method: Initial Dataset Release for Infrared-Driven Polymer Intelligence
No full textThis release provides the dataset used in the research paper "Infrared-Driven Polymer Intelligence: Predicting Thermal Properties from Spectroscopy with Machine Learning".
The dataset includes:
- FTIR spectra of various polymers
- Associated thermal property labels (Tg, Tm)
- Data format: '.csv' files
- Sample preprocessing scripts and documentationPlease see the associated paper
Dataset for "Attribution of credit in acknowledgements: The case of systematic reviews in medicine"
No full textThis anonymised database reports information on whether an author was 1) included in the author byline of the updated review and 2) omitted in the acknowledgements of the updated review.
It contains information for all the reviews published in the Cochrane Database of Systematic Reviews and that had been subject to an update as of June 2019, corresponding to 2,127 unique review-review pairs.
We removed from the sample 36 reviews in which the acknowledgements section was missing. This left us with 2,091 review pairs corresponding to 8,267 non-unique authors.
The final database report information for 7,752 authors for whom race, gender and publication information were available.Data collection methods are detailed in the "Attribution of credit in acknowledgements:
The case of systematic reviews in medicine" paper.STATA was used to create the data, and is required to view the .dta file
Dataset for "Zero-car households – constraint or lifestyle choice? A systematic literature review of the factors affecting non-car ownership"
No full textThe dataset contains details of 106 studies identified through a systematic review of literature. It shows the details of the study, a categorisation according to which of the five factors the study addresses: socio-demographic, psychological, life events, built environment and transport policies and services.A systematic literature review was undertaken according to a pre registered protoco
Dataset for "Covering one point process with another"
No full textFix a set A as a subset of Euclidean space (for example, a disc or a polygon), and a subset B contained in A (we often consider the case B=A).
Place n points X_1, ..., X_n in A, with the locations chosen independently and uniformly at random. We think of these as "transmitters".
Place another m points Y_1, ..., Y_m in B contained in A, which we think of as "receivers".
At each X_i, place a Euclidean ball of radius r.
We define R_{n,m,k} to be the smallest r such that every receiver Y_j has at least k transmitters within distance r.
In the paper "Covering one point process with another" we proved that if m/n tends to tau as n tends to infinity, then the quantity n R_{n,m,k}^d - c_1 log(n) - c_2 loglog(n) (for constants c_1,c_2 which we give in the paper) converges to a random variable (whose distribution we also give). These datasets include large numbers of independent samples of n R_{n,m,k}^d - c_1 log(n) - c_2 loglog(n).
The dataset is separated into files, and each file into rows. All the data in a given file are generated using fixed sets A and B, and parameters n, m, d, k. Each row in this given file is a single number: the outcome of an experiment, conducted independently of the other rows. In each experiment we place n points at random locations in A, place m points at random locations in B, calculate R_{n,m,k} as described above (and as detailed formally in the paper) and record the value of n R_{n,m,k}^d - c_1 log(n) - c_2 loglog(n) on a row. For the next row, we remove the existing points, and place n points in A, m points in B, etc. for the same n,m, A, B, but with the random points chosen independently of previous experiments.
In probabilisitic terms, the rows of a given file are independent and identically distributed random variables with a common distribution, which is the distribution of n R_{n,m,k}^d - c_1 log(n) - c_2 loglog(n).
The distribution depends on A, B, n, m, d and k. Different files were generated using different choices of A, B, n, m, d and k.
The paper was written by Frankie Higgs, Mathew D. Penrose and Xiaochuan Yang.
We thank Keith Briggs for suggesting the problem and advice on the simulations.The dataset were generated using computer random number generation to sample two sets of random points (X_1, ..., X_n) and (Y_1, ..., Y_m), and then the two-sample coverage threshold R_{n,m,k} was calculated for these random points by measuring the Euclidean distances between pairs |X_i - Y_j|.
This was implemented by the code available at https://github.com/frankiehiggs/CovXY (commit 4c4c086).The data was generated on a laptop computer using Python 3.Each csv file contains a number of rows. Every row in a given file was generated using the same sets A and B, and the same parameters n, m, d and k. The entry on one row is independent of the entries on every other row, as we performed the same experiment repeatedly with the same parameters, but sampling the random points independently each time
Dataset for "Magnetically-controlled Vortex Dynamics in a Ferromagnetic Superconductor"
No full textDatasets underpinning the five Figures and six Supplementary Figures for "Magnetically-controlled Vortex Dynamics in a Ferromagnetic Superconductor" in Communications Materials.
The primary data are a mixture of low temperature magnetisation data, taken using a SQUID magnetometer taken at the University of Bristol, and low temperature magnetic force microscopy (MFM) scan data taken at the University of Basel. Additionally, there are data derived from analysis of the magnetisation data, e.g. critical current, coercive field, as well as the results of magnetic relaxation measurements, i.e. Ueff. In addition to the MFM scan data are line profiles taken through regions of these scans.
The supplementary data include further magnetisation data, as well as examples of magnetic relaxation data. Additionally, there is a further example of a line profile taken from MFM scan data, along with corresponding fitted data.The dataset contains magnetisation and magnetic force microscopy data, with measurements performed on single crystals of the ferromagnetic iron-based superconductor EuFe2(As1-xPx)2, with x~0.21, Tc~24 K and T_FM~19 K.
Magnetisation data was collected using a Quantum Design SQUID magnetometer at the University of Bristol, at temperatures ranging from 5.0 to 25.0 K and magnetic fields ranging in magnitude up to 10,000 Oe (1 Tesla). The measurements were primarily in the form of magnetic hysteresis loops, with some further measurements of magnetic relaxation. From this data, quantities such as magnetic susceptibility, coercive field, critical current density and effective pinning potential are derived.
Magnetic force microscopy (MFM) data were acquired using a home-built oscillating magnetic nanowire microscope at the University of Basel. Scan data were acquired in temperatures ranging from approximately 22 K down to 4.3 K, and in magnetic fields ranging in magnitude up to 10,000 Oe (1 Tesla). Line profiles were derived from these 2D scan data.All data are in the form of .csv (comma separated values) with headers and units indicated. No specialist software is required to view the data
Dataset for "Understanding the role of aligned porosity on the intrinsic and extrinsic contributions to the dielectric permittivity of freeze-cast ferroelectrics"
No full textThis dataset is a part of the research article 'Understanding the role of aligned porosity on the intrinsic and extrinsic contributions to the dielectric permittivity of freeze-cast ferroelectric'. It contains comprehensive characterisation data for ferroelectric lead zirconate titanate PZT NCE51 ceramic, fabricated using both freeze-casting and conventional solid state route. This dataset contains hysteresis polarisation-electric field loops, impedance spectroscopy data and X-ray diffraction (XRD) patterns, which provide insights into how the microstructure of freeze-cast samples affect the functional properties of the porous freeze-cast ceramics.
In addition, the dataset also contains the results of finite element model, demonstrating how the local field distribution differ between the structures produced via freeze-casting and the burnt-out polymer spheres (BURPS) technique, despite having the same relative density. This difference demonstrate how the permittivity measured differ between these microstructures.
The dataset supports further analysis of the processing-microstructure-property relationships in porous ferroelectric ceramics. This may be of interest to researchers working on design and characterisation of advanced ferroelectric composites.Full details of the methodology can be found in Section 2 of the associate research article
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